Unveiling Epigenetic Regulatory Elements Associated with Breast Cancer Development.

ABSTRACT: Breast cancer affects over 2 million women annually and results in 650,000 deaths. This study aimed to identify epigenetic mechanisms impacting breast cancer-related gene expression, discover potential biomarkers, and present a novel approach integrating feature selection, Natural Language Processing, and 3D chromatin structure analysis. We used The Cancer Genome Atlas database with over 800 samples and multi-omics datasets (mRNA, miRNA, DNA methylation) to select 2701 features statistically significant in cancer versus control samples, from an initial 417,486, using the Monte Carlo Feature Selection and Interdependency Discovery algorithm. Classification of cancer vs. control samples on the selected features returned very high accuracy, depending on feature-type and classifier. The cancer

SUBMITTER: Jardanowska-Kotuniak M 

PROVIDER: S-EPMC12295874 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature